MAT 428 - Mathematical Foundations in Machine Learning

A broad introduction to machine learning by using the tools of basic knowledge of programming and probability theory, including classification; support vector machines; neural networks; clustering; feature selection; ensemble learning and reinforcement learning. The course will also discuss recent applications of machine learning, such as to computer science, data mining, bioinformatics and so on.

Prerequisite(s): 'C-' or better in MAT 221 and MAT 372.

3 credit(s).

Last Term Offered: not yet offered